In the context of sustainable development, energy optimization has become an essential field of investigation, due to its vital role in the preservation of environment and energy efficiency. Significantly, in the domain of building services and operation, HVAC (Heating, Ventilation, and Air Conditioning) systems are among the most energy-consuming elements. Examining the root causes for discomfort and addressing them by refining operation of HVAC systems, this paper offers a decision-making framework to alter HVAC performance to be more-human centric and energy efficient, driving the focus on how occupant's comfort and building controls interact together. This is done by investigating a deficiency in current practices regarding the cooling of open layout plans. Current methodologies of sorting spaces into thermal zones often neglect the variations and localized impact of factors such as shading from adjacent buildings, variating direct sunlight values in space, and other factors. Subsequently, minor fluctuations in temperature are often overlooked in thermal zoning. As a result, conventional HVAC systems prove insufficient in capturing the nuanced dynamics of local temperature variations, which leads to inaccurate monitoring and control. By applying the concept of multi-agent control system to HVAC controls, this study argues that each space has an Equilibrium Point (EP) which achieves optimum thermal conditions and approaches the cooling strategy in a human-centric approach. Moreover, this EP is floating to adapt to the nuances and minor fluctuations. The research explores the effectiveness and feasibility of EP controls through simulation. Integrating a Computational Fluid Dynamics (CFD) model, automated and optimized using Genetic Algorithms (GA), to search for optimum controls for space within given context simulating the floating EP to achieve sustainable operation of HVAC. This decision-making tool helped HVAC systems be more efficient and optimized in cooling open layout spaces with 60% less fluctuations in temperatures than ordinary configurations. This research directly contributes to achieving Sustainable Development Goals (SDGs) by enhancing energy efficiency and reducing environmental impact.